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\(\color{darkblue}{\textbf{Equity}}\)

  • Where does this data come from?
  • Why was this data collected?
  • How was this data generated?
  • Is this data demographically representative?
  • Who is included and who is excluded from this data?
  • Whose voices, lives, and experiences are missing?
  • How much can this data be disaggregated by race, gender, ethnicity, etc.?
  • Are the categories mutually exclusive and fully inclusive?
  • Are there “other” categories and, if so, who does that include?
  • Who stands to benefit from this data?
  • Who might be harmed by the collection or publication of this data?

(See more in Urban Institute’s Do No Harm Guide)

\(\color{darkblue}{\textbf{Basic Coding}}\)

\(\color{darkblue}{\textbf{Data}}\)

\(\color{dodgerblue}{\textbf{Importing}}\)


\(\color{dodgerblue}{\textbf{Cleaning}}\)


\(\color{dodgerblue}{\textbf{Other Languages}}\)

\(\color{darkblue}{\textbf{Visualization}}\)

\(\color{dodgerblue}{\textbf{Visualizing}}\)


\(\color{dodgerblue}{\textbf{Mapping}}\)

\(\color{darkblue}{\textbf{Analysis}}\)

\(\color{dodgerblue}{\textbf{Statistics}}\)


\(\color{dodgerblue}{\textbf{Machine Learning}}\)

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